U.S. patent number 11,447,152 [Application Number 16/751,487] was granted by the patent office on 2022-09-20 for system and methods for partially instrumented connected automated vehicle highway systems.
This patent grant is currently assigned to CAVH LLC. The grantee listed for this patent is CAVH LLC. Invention is credited to Tianyi Chen, Yang Cheng, Shuoxuan Dong, Shen Li, Xiaotian Li, Bin Ran, Kunsong Shi, Zhen Zhang, Yang Zhou.
United States Patent |
11,447,152 |
Ran , et al. |
September 20, 2022 |
System and methods for partially instrumented connected automated
vehicle highway systems
Abstract
The present technology relates to an intelligent road
infrastructure system and, more particularly, to systems and
methods for a heterogeneous connected automated vehicle highway
(CAVH) network in which the road network has various RSU and
TCU/TCC coverages and functionalities. The heterogeneous CAVH
network facilitates control and operations for vehicles of various
automation level and other road users by implementing various
levels of coordinated control among CAVH system entities and
providing individual road users with detailed customized
information and time-sensitive control instructions, and operations
and maintenance services.
Inventors: |
Ran; Bin (Fitchburg, WI),
Cheng; Yang (Middleton, WI), Chen; Tianyi (Madison,
WI), Zhou; Yang (Madison, WI), Zhang; Zhen (Madison,
WI), Li; Xiaotian (Madison, WI), Li; Shen (Madison,
WI), Dong; Shuoxuan (Madison, WI), Shi; Kunsong
(Madison, WI) |
Applicant: |
Name |
City |
State |
Country |
Type |
CAVH LLC |
Fitchburg |
WI |
US |
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Assignee: |
CAVH LLC (Fitchburg,
WI)
|
Family
ID: |
1000006572309 |
Appl.
No.: |
16/751,487 |
Filed: |
January 24, 2020 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20200239031 A1 |
Jul 30, 2020 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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62796618 |
Jan 25, 2019 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G08G
1/0125 (20130101); G08G 1/0116 (20130101); B60W
60/0011 (20200201); G08G 1/0112 (20130101); B60W
60/00184 (20200201); H04W 4/44 (20180201); H04W
4/46 (20180201) |
Current International
Class: |
B60W
60/00 (20200101); H04W 4/44 (20180101); G08G
1/01 (20060101); H04W 4/46 (20180101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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3559425 |
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Sep 2004 |
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JP |
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WO-2005037592 |
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Apr 2005 |
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WO |
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Other References
Society of Automotive Engineers International's new standard J3016:
"Taxonomy and Definitions for Terms Related to On-Road Motor
Vehicle Automated Driving Systems" 2014, downloaded Sep. 17, 2019,
12 pages. cited by applicant.
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Primary Examiner: Kan; Yuri
Attorney, Agent or Firm: Casimir Jones, S.C. Isenbarger;
Thomas A.
Parent Case Text
This application claims priority to U.S. provisional patent
application Ser. No. 62/796,618, filed Jan. 25, 2019, which is
incorporated herein by reference in its entirety.
Claims
We claim:
1. A vehicle operations and control system for a connected
automated vehicle highway (CAVH) network, said system comprising an
intelligent road infrastructure system (IRIS) comprising: a
roadside unit (RSU) network; and a Traffic Control Unit (TCU) and
Traffic Control Center (TCC) network, wherein the CAVH network
comprises RSU coverage and functionality and/or TCU/TCC coverage
and functionality; wherein the CAVH network is configured to:
provide control among system entities; provide road users with
customized information and control vehicles with vehicle specific
control instructions including vehicle longitudinal acceleration
and speed, lateral acceleration and speed, and vehicle orientation
and direction; and provide operations and maintenance services for
system entities wherein said RSUs comprise a communications module,
a sensing module, and a data processing module, and generate and
provide vehicle specific control instructions including vehicle
longitudinal acceleration and speed, lateral acceleration and
speed, and vehicle orientation and direction; and wherein said TCC
and TCU are automatic or semi-automated computational modules that
provide data gathering, information processing, network
optimization, and/or traffic control; and generate and provide
vehicle specific control instructions including longitudinal
acceleration and speed, lateral acceleration and speed, and vehicle
orientation and direction.
2. The system of claim 1 further comprising one or more of: vehicle
onboard units (OBU) and vehicle interfaces; traffic operations
centers (TOC); and/or a cloud-based platform configured to provide
information and computing services wherein said OBU is configured
to perform vehicle control functions by using: 1) the
communications device receiving vehicle control instructions for
longitudinal acceleration and speed, lateral acceleration and
speed, and vehicle orientation and direction; and 2) the vehicle
controller controlling vehicle longitudinal acceleration and speed,
lateral acceleration and speed, and vehicle orientation and
direction according to said vehicle control instructions; and
wherein TOC is automatic or semi-automated computational module
that provides data gathering, information processing, network
optimization, and/or traffic control.
3. The system of claim 1 wherein the system is configured to manage
mixed traffic of vehicles having heterogeneous automation levels,
non-automated vehicles, and other road users.
4. The system of claim 1 configured to provide sensing functions,
transportation behavior prediction and management functions,
planning and decision-making functions, and vehicle control
functions by generating and providing vehicle specific control
instructions including longitudinal acceleration and speed, lateral
acceleration and speed, and vehicle orientation and direction.
5. The system of claim 1 wherein the CAVH network comprises a
partially instrumented portion and/or a non-instrumented
portion.
6. The system of claim 1 comprising a partially instrumented RSU
providing one or more of the following types of functions:
communications functions, environment sensing functions, traffic
behavior prediction functions, and vehicle control functions,
wherein vehicle control functions comprise vehicle specific control
instructions including longitudinal acceleration and speed, lateral
acceleration and speed, and vehicle orientation and direction.
7. The system of claim 6 configured to sense a traffic environment
for an area comprising said partially instrumented RSU using data
from the partially instrumented RSU and data from other system
components communicated using cloud and infrastructure
communication.
8. The system of claim 1 configured to sense and communicate
traffic environment data for an area, said traffic environment data
describing vehicles; pedestrians; road geometry, road design
information and road pavement conditions; traffic control
infrastructure; traffic control devices; and/or animals.
9. The system of claim 4 wherein said transportation behavior
prediction and management functions are configured to predict
movement of mixed traffic of vehicles having heterogeneous
automation levels, non-automated vehicles, and/or other road users
based on information collected by and/or communicated from a
partially instrumented RSU, vehicle to vehicle communication,
and/or the cloud.
10. The system of claim 1 configured to provide a partially
instrumented transportation network.
11. The system of claim 1 configured to manage traffic and provide
vehicle instructions for vehicles in a traffic environment
comprising human-driven vehicles, autonomous vehicles, connected
vehicles, walking units, non-motor vehicles, connected autonomous
vehicles, and/or obstacles.
12. The system of claim 4 wherein said vehicle control functions
are configured to provide control instructions to: road
infrastructure; a human; a vehicle; and/or an animal or moving
obstacle.
13. The system of claim 4 wherein said vehicle control functions
comprise coordinated control strategies comprising full control
strategies, partial control strategies, and/or non-control
strategies.
14. The system of claim 12 wherein said vehicle control functions
provide microscopic control of an individual vehicle.
15. The system of claim 1 comprising one or more critical points
instrumented with one or more IRIS components to provide partial or
full control of the critical point.
16. The system of claim 1, wherein said system is a partially
instrumented CAVH system.
17. The system of claim 16 wherein said partially instrumented CAVH
system comprises IRIS components of varying functionality.
18. The system of claim 16 wherein said partially instrumented CAVH
system comprises IRIS components of varying hardware and/or
software configurations.
19. The system of claim 16 comprising an RSU providing
communications functions, environment sensing functions, traffic
behavior prediction functions, and/or vehicle control
functions.
20. The system of claim 16 comprising a TCC/TCU configured to make
decisions, globally optimize traffic, and/or control traffic.
21. The system of claim 1 configured to synchronize data in time or
space.
22. The system of claim 1 configured to coordinate control commands
sent to vehicles through OBU communication.
23. A method for coordinating vehicle movements comprising:
providing a connected automated vehicle highway (CAVH) network
comprising RSU coverage and functionality and/or TCU/TCC coverage
and functionality; and providing control among system entities,
providing road users with customized information, controlling
vehicles using time-sensitive control instructions, and providing
operations and maintenance services for system entities wherein
time-sensitive control instructions include vehicle longitudinal
acceleration and speed, lateral acceleration and speed, and vehicle
orientation and direction.
Description
FIELD
The present technology relates to systems and methods for a
heterogeneous connected automated vehicle highway (CAVH) network
comprising various roadside unit (RSU) and traffic control
unit/traffic control center (TCU/TCC) network coverages and
functionalities for vehicles of various automation levels and other
road users. The systems and methods provide various levels of
coordinated control among CAVH system entities, providing
individual road users with detailed customized information, and
time-sensitive control instructions and operations and maintenance
services.
BACKGROUND
Autonomous vehicles (e.g., vehicles that sense their environment
and navigate without human input or with reduced human input) are
in development. At present, autonomous vehicles are in experimental
testing and are not in widespread commercial use. Existing
autonomous vehicle technologies require expensive and complicated
onboard systems, which has substantially hindered the widespread
implementation and use of autonomous vehicles.
SUMMARY
In some embodiments, the present technology relates to connected
automated vehicle highway (CAVH) systems that coordinate vehicle
movements by communication of information and control commands
among vehicle subsystems and infrastructure subsystems. For
instance, U.S. patent application Ser. No. 15/628,331, which is
incorporated herein by reference, describes a system-oriented and
fully-controlled CAVH system that provides various levels of
connected and automated vehicles and highways. An additional
technology described in U.S. patent application Ser. No.
16/135,916, which is incorporated herein by reference, provides
systems and methods for an Intelligent Road Infrastructure System
(IRIS), which provides vehicle operations and control for CAVH
systems. While these technologies provide an autonomous driving
vehicle system based on fully instrumented CAVH roads, embodiments
of the present technology relate to CAVH systems comprising
autonomous and non-autonomous vehicles and/or comprising roads and
portions of roads for which various CAVH components and systems are
partially implemented. Thus, the technology described herein
provides a range of levels of coordinated vehicle control for
roads, e.g., embodiments provide systems comprising roads with
lower coverage and/or implementation of CAVH systems and components
that interface with roads with higher or full coverage and/or
implementation of CAVH systems and components. Embodiments provide
systems and methods for monitoring the movement of vehicles among
partially implemented CAVH portions of road systems and fully
implemented CAVH portions of road systems and for controlling the
movement of vehicles among partially implemented CAVH portions of
road systems and fully implemented CAVH portions of road
systems.
In some embodiments, the technology provides a CAVH system
comprising components and/or methods as described in U.S. patent
application Ser. No. 15/628,331, which is herein incorporated by
reference. For example, in some embodiments, the technology
provides a vehicle operations and control system for a connected
automated vehicle highway (CAVH) network. In some embodiments, the
system comprises an intelligent road infrastructure system (IRIS)
comprising a roadside unit (RSU) network and a Traffic Control Unit
(TCU) and Traffic Control Center (TCC) network, wherein the CAVH
network comprises various degrees of RSU coverage and functionality
and/or various degrees of TCU/TCC coverage and functionality; and
wherein the CAVH network is configured to provide various levels of
coordinated control among system entities, provides road users with
detailed customized information and time-sensitive control
instructions, and operations and maintenance services. In some
embodiments, the system further comprises one or more of vehicle
onboard units (OBU) and vehicle interfaces; traffic operations
centers (TOC); and/or a cloud-based platform configured to provide
information and computing services. In some embodiments, the system
is configured to manage mixed traffic of vehicles having various
automation levels, non-automated vehicles, and other road
users.
In some embodiments, the system is configured to provide sensing
functions, transportation behavior prediction and management
functions, planning and decision-making functions, and vehicle
control functions.
In some embodiments, the CAVH network comprises a partially
instrumented portion and/or a non-instrumented portion. In some
embodiments, the CAVH network further comprises a fully
instrumented portion.
In some embodiments, the technology provides a partially
instrumented RSU providing one or more, two or more, or three or
more of the following: communications functions, environment
sensing functions, traffic behavior prediction functions, or
vehicle control functions. In some embodiments, systems comprise a
partially instrumented RSU providing one or more, two or more, or
three or more of the following: communications functions,
environment sensing functions, traffic behavior prediction
functions, or vehicle control functions. In some embodiments, the
technology provides a fully instrumented RSU providing
communications functions, environment sensing functions, traffic
behavior prediction functions, and vehicle control functions. In
some embodiments, systems comprise a fully instrumented RSU
providing communications functions, environment sensing functions,
traffic behavior prediction functions, and vehicle control
functions. In some embodiments, the system as described herein
comprise a partially instrumented RSU and the system is configured
to sense the traffic environment for an area comprising said
partially instrumented RSU using data from the partially
instrumented RSU and data from other system components communicated
using cloud and infrastructure communication.
In some embodiments, the system is configured to sense and
communicate traffic environment data for an area, said traffic
environment data describing vehicles; pedestrians; road geometry,
road design information, and road pavement conditions; traffic
control infrastructure; traffic control devices; and/or animals. In
some embodiments, the traffic control infrastructure comprises
safety barriers and/or road markings. In some embodiments, the
traffic control devices comprise traffic signs and/or traffic
signals.
In some embodiments, the system comprises transportation behavior
prediction and management functions that are configured to predict
individual human-driven vehicular trajectory; vehicle platoon
and/or mixed platoon trajectory; vehicular route choice; traffic
flow over transportation segment; pedestrian behavior; general
traffic environment; vehicle traffic composition; and/or vehicle
and infrastructure communication connection. In some embodiments,
transportation behavior prediction and management functions are
configured to predict based on information collected by and/or
communicated from a partially instrumented RSU, vehicle to vehicle
communication, and/or the cloud. In some embodiments, general
traffic environment comprises data describing weather, traffic
conditions, traffic hazards, time, and/or location.
In some embodiments, the system integrates real-time sensor data,
interpolated data, and predicted transportation behavior to provide
partial or full CAVH functionality.
In some embodiments, the systems described herein comprise planning
and decision-making functions that are configured to plan and/or
decide vehicle and/or platoon trajectory; vehicle and/or platoon
route choice; variable speed limit; ramp metering; vehicle use of
on-ramp and/or off-ramp; and/or traffic signal timing. In some
embodiments, the planning and decision-making functions are
configured to plan and/or decide based on information collected by
and/or communicated from a partially instrumented RSU. In some
embodiments, a TCC/TCU processes information from a partially
instrumented RSU, executes a planning and decision-making function
to plan and/or decide vehicle and/or platoon trajectory; vehicle
and/or platoon route choice; variable speed limit; ramp metering;
vehicle use of on-ramp and/or off-ramp; and/or traffic signal
timing, and to communicate instructions to a TCU and/or a
vehicle.
In some embodiments, the systems provided herein are configured to
provide a fully instrumented transportation network. In some
embodiments, the systems provided herein are configured to provide
a partially instrumented transportation networks. In some
embodiments, the systems described herein comprise subsystems that
are fully instrumented, partially instrumented, and/or
non-instrumented. In some embodiments, a non-instrumented subsystem
is configured to communicate with other components (e.g., a
non-instrumented subsystem is configured to send and receive
information to and from other components).
In some embodiments, the systems described herein are configured to
manage traffic and provide vehicle instructions for vehicles in a
traffic environment comprising mixed traffic and non-traffic units
that are human-driven vehicles, autonomous vehicles, connected
vehicles, walking units, non-motor vehicles, connected autonomous
vehicles, and obstacles.
In some embodiments, the systems are configured to provide vehicle
control functions. In some embodiments, the vehicle control
functions are configured to provide control instructions to road
infrastructure; humans; vehicles; and/or animals and moving
obstacles. In some embodiments, the road infrastructure is a
traffic sign, an IRIS component, a traffic signal, or a traffic
control device. In some embodiments, the human being is a
pedestrian or is a vehicle user. In some embodiments, the vehicle
is an autonomous vehicle, a connected vehicle, a connected
autonomous vehicle, a human-driven vehicle, or a non-motor vehicle.
In some embodiments, the vehicle control functions comprise
coordinated control strategies comprising full control strategies,
partial control strategies, and/or non-control strategies. In some
embodiments, a non-control strategy includes communication of
information among components of the system (e.g., information is
communicated).
In some embodiments, the vehicle control functions are configured
to receive information describing the CAVH configuration and sensor
information. In some embodiments, the information describing the
CAVH configuration comprises information describing RSU location
and/or RSU function. In some embodiments, the sensor information
comprises sensed static object information from an RSU and/or
sensed dynamic object information. In some embodiments, the sensor
information comprises real-time traffic information and/or accident
or special event information. In some embodiments, the information
describing the CAVH configuration comprises control levels. In some
embodiments, the vehicle control functions are configured to
receive information comprising decision maker instructions and/or
recommendations. In some embodiments, the vehicle control functions
are configured to receive information from an RSU, the TCC/TCU,
and/or cloud. In some embodiments, the vehicle control functions
provide macroscopic control of traffic flow or density on road
segments or road networks. In some embodiments, the macroscopic
control of vehicles comprises determining vehicle route. In some
embodiments, the vehicle control functions provide mesoscopic
control of vehicle platooning. In some embodiments, the vehicle
control functions provide microscopic control of an individual
vehicle. In some embodiments, microscopic control of individual
vehicle comprises longitudinal control and lateral control of a
vehicle. In some embodiments, longitudinal control comprises
control of vehicle following and/or collision avoidance. In some
embodiments, lateral control comprises control of vehicle merging,
lane changing, diverging, and/or turning.
In some embodiments, the systems described herein comprise one or
more critical points. In some embodiments, a critical point is a
static critical point or a dynamic critical point. In some
embodiments, a critical point is identified as a region or point of
a road having a high historical crash frequency, traffic control
signage, a traffic control sign, traffic congestion, a critical
road geometry (e.g., a curve, hill, blind spot, merge point, on
ramp, off ramp, toll collection point (e.g., toll booth, toll
plaza), or traffic circle), a traffic oscillation, and/or a
real-time traffic incident (e.g., an ongoing traffic accident). In
some embodiments, a critical point is instrumented with one or more
IRIS components to provide partial or full control of the critical
point. In some embodiments, critical points are identified as
regions or points of roads that have high priority for traffic
control and management.
In some embodiments, systems further comprise safety infrastructure
and software to minimize and/or eliminate crash frequency and
severity. In some embodiments, the safety infrastructure and
software comprises proactive methods based on incident prediction
and risk index estimation that are used before a traffic incident
occurs; active methods based on rapid incident detection that are
used to identify imminent incidents and are deployed before harms
occur; and/or passive methods to alleviate harms and losses after
an incident occurs.
In some embodiments, the systems provided herein are a partially
instrumented CAVH system. In some embodiments, a partially
instrumented CAVH system comprises IRIS components of varying
functionality. In some embodiments, a partially instrumented CAVH
system comprises IRIS components of varying hardware and/or
software configurations. In some embodiments, a system comprises a
fully instrumented RSU providing communications functions,
environment sensing functions, traffic behavior prediction
functions, and vehicle control functions. In some embodiments, a
system comprises a partially instrumented RSU providing
communications functions. In some embodiments, a system comprises a
partially instrumented RSU providing environment sensing functions.
In some embodiments, a system comprises a partially instrumented
RSU providing traffic behavior prediction functions. In some
embodiments, a system comprises a partially instrumented RSU
providing vehicle control functions. In some embodiments, a system
comprises a RSU providing two of the following: communications
functions, environment sensing functions, traffic behavior
prediction functions, and vehicle control functions. In some
embodiments, a system comprises a RSU providing three of the
following: communications functions, environment sensing functions,
traffic behavior prediction functions, and vehicle control
functions. In some embodiments, the system comprises a TCC/TCU
configured to make decisions, globally optimize traffic, and/or
control traffic. In some embodiments, the system comprises a
TCC/TCU configured to make decisions. In some embodiments, the
system comprises a TCC/TCU configured to globally optimize traffic.
In some embodiments, the system comprises a TCC/TCU configured to
control traffic. In some embodiments, the system comprises a
TCC/TCU configured to perform any two of: make decisions, globally
optimize traffic, and/or control traffic.
In some embodiments, the system is configured to synchronize data
in time or space. In some embodiments, the system is configured to
synchronize timestamps and align locations of data within and
between sensors. In some embodiments, the system is configured to
synchronize data from computing and communication modules in time
and space. In some embodiments, the system is configured to
coordinate control commands sent to vehicles through OBU
communication.
Also provided herein are methods employing any of the systems
described herein for the management of one or more aspects of
traffic control. The methods include those processes undertaken by
individual participants in the system (e.g., drivers, public or
private local, regional, or national transportation facilitators,
government agencies, etc.) as well as collective activities of one
or more participants working in coordination or independently from
each other.
For instance, in some embodiments, the technology provides a method
for coordinating vehicle movements comprising providing a connected
automated vehicle highway (CAVH) network comprising heterogeneous
degrees of RSU coverage and functionality and/or heterogeneous
degrees of TCU/TCC coverage and functionality; and providing levels
of coordinated control among system entities, providing road users
with customized information and time-sensitive control
instructions, and providing operations and maintenance services. In
some embodiments, the methods further comprise providing one or
more of: vehicle onboard units (OBU) and vehicle interfaces;
traffic operations centers (TOC); and/or a cloud-based platform
configured to provide information and computing services. In some
embodiments, methods comprise managing mixed traffic of vehicles
having heterogeneous automation levels, non-automated vehicles, and
other road users. In some embodiments, methods further comprise
sensing the environment, predicting and managing transportation
behavior, planning and making decisions, and controlling
vehicles.
In some embodiments, the methods find use to manage traffic in a
CAVH network comprising a partially instrumented portion and/or a
non-instrumented portion. In some embodiments, the methods find use
to manage traffic in a CAVH network further comprising a fully
instrumented portion. In some embodiments, the CAVH network
comprises a partially instrumented portion and said method
comprises communicating, environment sensing, predicting traffic
behavior, or controlling vehicles. In some embodiments, methods
comprise sensing the traffic environment for said partially
instrumented portion; and using data from the partially
instrumented portion and data from other system components
communicated using cloud and infrastructure communication. In some
embodiments, methods comprise sensing and communicating traffic
environment data for an area, said traffic environment data
describing vehicles; pedestrians; road geometry, road design
information, and road pavement conditions; traffic control
infrastructure; traffic control devices; and/or animals. In some
embodiments, traffic control infrastructure comprises safety
barriers and/or road markings. In some embodiments, traffic control
devices comprise traffic signs and/or traffic signals.
In some embodiments, methods comprising predicting and managing
transportation behavior comprise predicting, e.g., individual
human-driven vehicular trajectory; mixed platoon trajectory;
vehicular route choice; traffic flow over transportation segment;
pedestrian behavior; general traffic environment; vehicle traffic
composition; and/or vehicle and infrastructure communication
connection. In some embodiments, predicting and managing
transportation behavior comprises predicting based on information
collected by and/or communicated from a partially instrumented RSU,
vehicle to vehicle communication, and/or the cloud. In some
embodiments, general traffic environment comprises data describing
weather, traffic conditions, traffic hazards, time, and/or
location. In some embodiments, methods comprise integrating
real-time sensor data, interpolated data, and predicted
transportation behavior to provide partial or full CAVH
functionality.
In some embodiments, methods comprising planning and making
decisions comprise planning and/or deciding, e.g., vehicle and/or
platoon trajectory; vehicle and/or platoon route choice; variable
speed limit; ramp metering; vehicle use of on-ramp and/or off-ramp;
and/or traffic signal timing. In some embodiments, planning and
making decisions comprises collecting information by a partially
instrumented RSU and/or communicating information to or from a
partially instrumented RSU.
In some embodiments, methods comprise processing information from a
partially instrumented RSU and deciding, e.g., vehicle and/or
platoon trajectory; vehicle and/or platoon route choice; variable
speed limit; ramp metering; vehicle use of on-ramp and/or off-ramp;
and/or traffic signal timing; and communicating instructions to a
TCU and/or a vehicle. In some embodiments, methods comprise
providing a fully instrumented transportation network. In some
embodiments, methods comprise providing a partially instrumented
transportation network. In some embodiments, methods comprise
providing a non-instrumented transportation network. In some
embodiments, methods comprise managing traffic and providing
vehicle instructions for vehicles in a traffic environment
comprising mixed traffic and non-traffic units that are
human-driven vehicles, autonomous vehicles, connected vehicles,
walking units, non-motor vehicles, connected autonomous vehicles,
and obstacles. In some embodiments, controlling vehicles comprises
providing control instructions to: road infrastructure; humans;
vehicles; and/or animals and moving obstacles. In some embodiments,
road infrastructure is a traffic sign, an IRIS component, a traffic
signal, or a traffic control device.
In some embodiments, a human is a pedestrian or is a vehicle user.
In some embodiments, a vehicle is an autonomous vehicle, a
connected vehicle, a connected autonomous vehicle, a human-driven
vehicle, or a non-motor vehicle. In some embodiments, controlling
vehicles comprises providing coordinated control strategies that
are full control strategies, partial control strategies, and/or
non-control strategies. In some embodiments, controlling vehicles
comprises receiving information describing the CAVH configuration
and sensor information. In some embodiments, information describing
the CAVH configuration comprises information describing RSU
location and/or RSU function. In some embodiments, sensor
information comprises sensed static object information from an RSU
and/or sensed dynamic object information. In some embodiments,
sensor information comprises real-time traffic information and/or
accident or special event information. In some embodiments,
information describing the CAVH configuration comprises control
levels. In some embodiments, controlling vehicles comprises
receiving information comprising decision maker instructions and/or
recommendations. In some embodiments, controlling vehicles
comprises receiving information from an RSU, the TCC/TCU, and/or
cloud.
In some embodiments, controlling vehicles comprises macroscopically
controlling traffic flow or density on road segments or road
networks. In some embodiments, macroscopically controlling vehicles
comprises determining vehicle route. In some embodiments,
controlling vehicles comprises mesoscopically controlling vehicle
platooning. In some embodiments, controlling vehicles comprises
microscopically controlling individual vehicles. In some
embodiments, microscopically controlling individual vehicles
comprises longitudinally controlling and laterally controlling a
vehicle. In some embodiments, longitudinally controlling a vehicle
comprises controlling vehicle following and/or avoiding collisions.
In some embodiments, laterally controlling a vehicle comprises
controlling vehicle merging, lane changing, diverging, and/or
turning.
In some embodiments, methods comprise coordinating vehicle
movements at one or more critical points. In some embodiments, a
critical point is a static critical point or a dynamic critical
point. In some embodiments, a critical point is a static critical
point or a dynamic critical point. In some embodiments, a critical
point is identified as a region or point of a road having a high
historical crash frequency, traffic control signage, a traffic
control sign, traffic congestion, a critical road geometry (e.g., a
curve, hill, blind spot, merge point, on ramp, off ramp, toll, or
traffic circle), a traffic oscillation, and/or a real-time traffic
incident (e.g., an ongoing traffic accident). In some embodiments,
methods comprises instrumenting a critical point with one or more
IRIS components to provide partial or full control of the critical
point. In some embodiments, methods comprise identifying critical
points as regions or points of roads that have high priority for
traffic control and management.
In some embodiments, methods further comprise providing safety
infrastructure and software to minimize and/or eliminate crash
frequency and severity. In some embodiments, safety infrastructure
and software comprises, e.g., proactive methods based on incident
prediction and risk index estimation that are used before a traffic
incident occurs; active methods based on rapid incident detection
that are used to identify imminent incidents and are deployed
before harms occur; and/or passive methods to alleviate harms and
losses after an incident occurs.
In some embodiments, methods comprise controlling vehicle movements
in a partially instrumented CAVH system. In some embodiments, a
partially instrumented CAVH system comprises IRIS components of
heterogeneous functionality. In some embodiments, a partially
instrumented CAVH system comprises IRIS components of heterogeneous
hardware and/or software configurations. In some embodiments,
methods comprise controlling vehicle movements by a fully
instrumented RSU or a partially instrumented RSU. In some
embodiments, controlling vehicle movements in a fully instrumented
RSU comprises communicating, sensing the environment, predicting
traffic behavior, and controlling vehicles. In some embodiments,
the communicating is performed by an RSU. In some embodiments,
sensing the environment is performed by an RSU. In some
embodiments, predicting traffic behavior is performed by an RSU. In
some embodiments, controlling vehicles is performed by an RSU. In
some embodiments, two of communicating, sensing the environment,
predicting traffic behavior, and controlling vehicles is performed
by a partially instrumented RSU. In some embodiments, three of
communicating, sensing the environment, predicting traffic
behavior, and controlling vehicles is performed by a partially
instrumented RSU.
In some embodiments, methods comprise making decisions, globally
optimizing traffic, and/or controlling traffic by a TCC/TCU. In
some embodiments, methods comprise making decisions by a TCC/TCU.
In some embodiments, methods comprise globally optimizing traffic
by a TCC/TCU. In some embodiments, methods comprise controlling
traffic by a TCC/TCU. In some embodiments, methods comprise two of
making decisions, globally optimizing traffic, and/or controlling
traffic is performed by a TCC/TCU.
Some embodiments of methods comprise synchronizing data in time or
space. In some embodiments, methods comprise synchronizing
timestamps and aligning locations of data within and between
sensors. In some embodiments, methods comprise synchronizing data
from computing and communication modules in time and space. In some
embodiments, methods comprise coordinating control commands sent to
vehicles through OBU communication.
In some embodiments, the technology provides use of a partially
instrumented CAVH system to control traffic flow and vehicle
movement. In some embodiments, the technology provides use of a
system or a method as described herein.
Some portions of this description describe the embodiments of the
technology in terms of algorithms and symbolic representations of
operations on information. These algorithmic descriptions and
representations are commonly used by those skilled in the data
processing arts to convey the substance of their work effectively
to others skilled in the art. These operations, while described
functionally, computationally, or logically, are understood to be
implemented by computer programs or equivalent electrical circuits,
microcode, or the like. Furthermore, it has also proven convenient
at times to refer to these arrangements of operations as modules
without loss of generality. The described operations and their
associated modules may be embodied in software, firmware, hardware,
or any combinations thereof.
Certain steps, operations, or processes described herein may be
performed or implemented with one or more hardware or software
modules, alone or in combination with other devices. In one
embodiment, a software module is implemented with a computer
program product comprising a computer-readable medium containing
computer program code, which can be executed by a computer
processor for performing any or all steps, operations, or processes
described.
Embodiments of the technology may also relate to an apparatus for
performing the operations described herein. This apparatus may be
specially constructed for the required purposes and/or it may
comprise a general-purpose computing device selectively activated
or reconfigured by a computer program stored in the computer. Such
a computer program may be stored in a non-transitory, tangible
computer readable storage medium or any type of media suitable for
storing electronic instructions, which may be coupled to a computer
system bus. Furthermore, any computing systems referred to in the
specification may include a single processor or may be
architectures employing multiple processor designs for increased
computing capability.
Additional embodiments will be apparent to persons skilled in the
relevant art based on the teachings contained herein.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a schematic drawing showing an embodiment of a CAVH
system comprising CAVH system components and roads comprising
critical points. Features of the technology shown in FIG. 1
include, e.g., 101: Traffic Control Center/Traffic Operation Center
(TCC/TOC), which collects data from Traffic Control Units (TCUs)
102. Based on the data, the TCC/TOC provides a macroscopic control
computation and/or instruction (e.g., route choice) and sends
information and/or control instructions to the TCU. The TCU 102
aggregates and integrates information collected by one or more
Roadside Units (RSU) 103 and sends the fused data to TCC/TOC. TCU
also receives control instructions from TCC/TOC. TCU generates a
mesoscopic control strategy (e.g., vehicular platooning) based on
the information and/or control instructions received from the
TCC/TOC. TCU sends the strategy to RSU. One or more RSU 103
receives data from connected vehicles, detects traffic conditions,
and/or sends targeted instructions to vehicles. RSU receives
control strategies from TCU and sends instructions to local
vehicles based on the strategy. FIG. 1 shows an embodiment of a
CAVH system comprising roads that have critical points: e.g., Stop
Sign Critical Point 104, which is a location or region identified
as having a stop sign, e.g., at a crossing; Traffic Signal Critical
Point 105, which is a location or region identified as having a
traffic signal, e.g., at a crossing; Traffic Oscillation Critical
Point 106, which is a location or region identified as having
significant traffic oscillations (e.g., variation in amount of
traffic as a function of time); and Traffic Capacity Critical Point
107, which is a location or region identified as having a high
average traffic capacity.
FIG. 2 is a block diagram showing an embodiment of the technology
related to information flow for coordinated control of vehicles.
Features of the technology shown in FIG. 2 include, e.g., an RSU
201, TCC/TCU 202, cloud or other sources 203, and a control module
unit 204 (e.g., inside the RSU). The RSU is configured to receive
data from connected vehicles, detect traffic conditions, and send
targeted instructions to vehicles. RSU receives a control strategy
from TCU and sends instructions to local vehicles based on the
strategy.
FIG. 3 is a flowchart of an exemplary method embodiment of the
technology. The exemplary method identifies critical points on
roads, e.g., by identifying dynamic and static characteristics of
vehicles (e.g., automated and non-automated vehicles) and other
entities (e.g., people, objects) using a road or near a road.
FIG. 4 is a block diagram showing an embodiment of the technology
for synchronizing sensor data in space and/or in time. Features of
the technology shown in FIG. 4 include, e.g., one or more Sensors
401 (e.g., devices that sense the environment and/or surroundings);
a Synchronization module 402 (e.g., a unit inside a TCC/TCU or RSU)
that synchronizes data from sensors in time and/or in space; and a
Control module 403 (e.g., a Control unit inside RSU). Data
synchronization in time refers to identifying first data from a
first sensor and second data from a second sensor occurred at the
same time (or at substantially or effectively the same time). Data
synchronization in space refers to identifying first data from a
first sensor and second data from a second sensor occurred at the
same location (or at substantially or effectively the same
location).
FIG. 5 is a schematic drawing showing an embodiment of the
technology at a traffic signal critical point. Features of the
technology shown in FIG. 5 include, e.g., Communication between
vehicles and RSU 501; Limited function RSU 502; Non-CAVH vehicle
identified to have critical movement 503; CAVH vehicle identified
to have critical movement 504; Non-CAVH vehicle identified to have
non-critical movement 505; CAVH vehicle identified to have
non-critical movement 506; and a Signal Controller 507.
FIG. 6 is a schematic drawing showing an embodiment of the
technology at a stop sign critical point. Features of the
technology shown in FIG. 6 include, e.g., Communication (e.g.,
wireless communication) between RSU and vehicles 601; Limited
function RSU 602; and vehicle travel trajectory 603.
FIG. 7 is a schematic drawing showing an embodiment of the
technology at a roundabout critical point. Features of the
technology shown in FIG. 7 include, e.g., Communication (e.g.,
wireless communication) among CAVH components and connected
vehicles 701; trajectory for connected vehicles 702; trajectories
for normal vehicles 703; and an RSU 704.
DEFINITIONS
To facilitate an understanding of the present technology, terms and
phrases are defined below. Additional definitions are set forth
throughout the detailed description.
Throughout the specification and claims, the following terms take
the meanings explicitly associated herein, unless the context
clearly dictates otherwise. The phrase "in one embodiment" as used
herein does not necessarily refer to the same embodiment, though it
may. Furthermore, the phrase "in another embodiment" as used herein
does not necessarily refer to a different embodiment, although it
may. Thus, as described below, various embodiments of the invention
may be readily combined, without departing from the scope or spirit
of the invention.
In addition, as used herein, the term "or" is an inclusive "or"
operator and is equivalent to the term "and/or" unless the context
clearly dictates otherwise. The term "based on" is not exclusive
and allows for being based on additional factors not described,
unless the context clearly dictates otherwise. In addition,
throughout the specification, the meaning of "a", "an", and "the"
include plural references. The meaning of "in" includes "in" and
"on."
As used herein, the terms "about", "approximately",
"substantially", and "significantly" are understood by persons of
ordinary skill in the art and will vary to some extent on the
context in which they are used. If there are uses of these terms
that are not clear to persons of ordinary skill in the art given
the context in which they are used, "about" and "approximately"
mean plus or minus less than or equal to 10% of the particular term
and "substantially" and "significantly" mean plus or minus greater
than 10% of the particular term.
As used herein, the suffix "-free" refers to an embodiment of the
technology that omits the feature of the base root of the word to
which "-free" is appended. That is, the term "X-free" as used
herein means "without X", where X is a feature of the technology
omitted in the "X-free" technology. For example, a "sensing-free"
method does not comprise a sensing step, a "controller-free" system
does not comprise a controller, etc.
As used herein, the term "support" when used in reference to one or
more components of the CAVH system providing support to and/or
supporting one or more other components of the CAVH system refers
to, e.g., exchange of information and/or data between components
and/or levels of the CAVH system, sending and/or receiving
instructions between components and/or levels of the CAVH system,
and/or other interaction between components and/or levels of the
CAVH system that provide functions such as information exchange,
data transfer, messaging, and/or alerting.
As used herein, the term "fully instrumented" refers to a CAVH
system or a portion of a CAVH system comprising all IRIS system
components and all IRIS system functions (e.g., all of: sensing
functions, transportation behavior prediction and management
functions, planning and decision-making functions, and vehicle
control functions).
As used herein, the term "partially instrumented" refers to a CAVH
system or a portion of a CAVH system comprising some, but not all,
IRIS system components and/or some, but not all, IRIS system
functions (e.g., some, but not all of, sensing functions,
transportation behavior prediction and management functions,
planning and decision-making functions, and vehicle control
functions).
As used herein, the term "non-instrumented" refers to a road system
or a portion of a road system (e.g., a road system or portion
interfacing with a fully instrument and/or a partially instrumented
CAVH system or portion of a CAVH system) that comprises no IRIS
system components and does not comprise (e.g., is not served by)
IRIS system functions. In some embodiments, a "non-instrumented"
system provides communications and information exchange.
As used herein, the term "full control" refers to a control
function or control strategy of a CAVH system in which all vehicles
have automation functions and are configured to receive and
implement control orders in a cooperative manner; and in which all
infrastructure components (e.g., traffic signal, variable speed
limit sign, etc.) are configured to be controlled, if necessary, in
a cooperative manner.
As used herein, the term "partial control" refers to a control
function or control strategy of a CAVH system in which all or some
of the vehicles are configured to receive control orders and
implement control orders in a noncooperative and/or cooperative
manner; and/or in which all or some of the infrastructure
components are configured to be controlled in a noncooperative
and/or cooperative manner.
As used herein, the term "non-control" refers to a control function
or control strategy of a CAVH system in which none of vehicles are
configured to be controlled and in which none of the infrastructure
components is configured to be controlled. In some embodiments, a
non-control strategy comprises communication and exchange of
information.
As used herein, the term "IRIS system component" refers
individually and/or collectively to one or more of an OBU, RSU,
TCC, TCU, TCC/TCU, TOC, and/or CAVH cloud component.
As used herein, the term "critical point" refers to a portion or
region of a road that is identified as appropriate to be provided
with a partially implemented CAVH system or a fully implemented
CAVH system. In some embodiments, a critical point is categorized
as a "static critical point" and in some embodiments, a critical
point is categorized as a "dynamic critical point". As used herein,
a "static critical point" is a point (e.g., region or location) of
a road that is a critical point based on identification of road
and/or traffic conditions that are generally constant or that
change very slowly (e.g., on a time scale longer than a day, a
week, or a month) or only by planned reconstruction of
infrastructure. As used herein, a "dynamic critical point" is a
point (e.g., region or location) of a road that is a critical point
based on identification of road conditions that change (e.g.,
predictably or not predictably) with time (e.g., on a time scale of
an hour, a day, a week, or a month). Critical points based on
historical crash data, traffic signs, traffic signals, traffic
capacity, and road geometry are exemplary static critical points.
Critical points based on traffic oscillations, real-time traffic
management, or real-time traffic incidents are exemplary dynamic
critical points.
In some embodiments, critical points are identified using, e.g.,
historical crash data (e.g., the top 20% (e.g., top 15-25% (e.g.,
top 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25%)) most frequent
crash points in a road system are identified as critical points);
traffic signs (e.g., where certain traffic signs (e.g.,
accident-prone areas) are detected are identified as critical
points); traffic capacity (e.g., the top 20% (e.g., top 15-25%
(e.g., top 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25%)) highest
traffic capacity areas are identified as critical points); road
geometry (e.g., roads with critical road geometry (e.g., curves,
blind spots, hills, intersections (e.g., signalized intersections,
stop sign intersections, yield sign intersections), roundabouts)
are identified as critical points); traffic oscillation (e.g.,
points with significant traffic oscillations are identified as
critical points); real-time traffic management (e.g., points with
potential traffic management are identified as critical points);
and/or real-time traffic incident (e.g., points with traffic
incidents (e.g., accident, crash, congestion, construction or
maintenance, weather-related event, etc.) or vehicle malfunction
are identified as critical points).
As used herein, the term "data synchronization" refers to
identifying data from one or more sensors that was collected at the
same time, substantially same time, and/or effectively the same
time ("synchronized in time") or at the same location,
substantially the same location, and/or effectively the same
location ("synchronized in space").
As used herein, the term "human-driven vehicles" refers to vehicles
that are controlled by a human.
As used herein, the term "autonomous vehicle" or "AV" refers to an
autonomous vehicle, e.g., at any level of automation (e.g., as
defined by SAE International Standard J3016 (2014)).
As used herein, the term "connected vehicle" or "CV" refers to a
connected vehicle, e.g., configured for any level of communication
(e.g., V2V, V2I, and/or I2V).
As used herein, the term "walking unit" refers to any walking
creature, e.g., a human pedestrian or an animal.
As used herein, the term "non-motor vehicle" refers to an
animal-powered vehicle, e.g., a bicycle, tricycle, scooter,
carriage, cart, rickshaw, skateboard, etc.
As used herein, the term "connected autonomous vehicle" or "CAV"
refers to a connected autonomous vehicle having any level of
automation (e.g., as defined by SAE International Standard J3016
(2014)) and communication (e.g., V2V, V2I, and/or I2V).
DETAILED DESCRIPTION
In some embodiments, the present technology relates to an
intelligent road infrastructure system and, more particularly, to
systems and methods for a heterogeneous connected automated vehicle
highway (CAVH) network in which the road network has various RSU
and TCU/TCC coverages and functionalities. The heterogeneous CAVH
network facilitates control and operations for vehicles of various
automation level and other road users by implementing various
levels of coordinated control among CAVH system entities and
providing individual road users with detailed customized
information and time-sensitive control instructions, and operations
and maintenance services.
In some embodiments, the technology provides a vehicle operations
and control system comprising one or more of a roadside unit (RSU)
network; a Traffic Control Unit (TCU) and Traffic Control Center
(TCC) network (e.g., TCU/TCC network); a vehicle comprising an
onboard unit (OBU); and/or a Traffic Operations Center (TOC).
Embodiments provide an RSU network comprising one or more RSUs. In
some embodiments, RSUs have a variety of functionalities. For
example, embodiments of RSUs comprise one or more components,
sensors, and/or modules as described herein in relation to the RSU.
In some embodiments, an RSU is a "limited function RSU", which is
an RSU comprising fewer components, sensors, and/or modules that a
"full function" RSU. Embodiments of the technology provide several
types of limited function RSUs and several types of full function
RSUs. The technology provides several levels of RSUs, e.g., from
low to high comprising fewer or more components, sensors, modules,
and/or functionalities. For example, in some embodiments RSUs
provide real-time vehicle environment sensing and traffic behavior
prediction and send instantaneous control instructions for
individual vehicles through OBUs. In some embodiments, RSUs provide
real-time vehicle environment sensing and traffic behavior
prediction and do not send instantaneous control instructions for
individual vehicles through OBUs. In some embodiments, RSUs do not
provide real-time vehicle environment sensing and traffic behavior
prediction and send instantaneous control instructions for
individual vehicles through OBUs. In some embodiments, RSUs provide
real-time vehicle environment sensing and do not provide traffic
behavior prediction. In some embodiments, RSUs do not provide
real-time vehicle environment sensing and provide traffic behavior
prediction. In some embodiments, RSUs provide real-time vehicle
environment sensing based on a limited number of sensors, modules,
and/or functionalities described herein. In some embodiments, RSUs
provide real-time vehicle environment sensing based on 1, 2, 3, 4,
5, 6, 7, 8, 9, or 10 sensors, modules, and/or functionalities
described herein.
As described herein, in some embodiments, full function RSUs or
RSUs with higher levels of function are placed at or near critical
points to monitor critical points, collect data from critical
points, and manage vehicles at critical points. As described
herein, in some embodiments, limited function RSUs are placed at
non-critical points, e.g., to conserve resources, for efficient use
of power and communications bandwidth, and to reduce the cost of
installation of a CAVH system.
In some embodiments, the technology provides a system (e.g., a
vehicle operations and control system comprising one or more of an
RSU network; a TCU/TCC network; a vehicle comprising an onboard
unit OBU; a TOC; and a cloud-based platform configured to provide
information and computing services; see, e.g., U.S. Provisional
Patent Application Ser. No. 62/691,391, incorporated herein by
reference in its entirety) configured to provide sensing functions,
transportation behavior prediction and management functions,
planning and decision making functions, and/or vehicle control
functions. In some embodiments, the system comprises wired and/or
wireless communications media. In some embodiments, the system
comprises a power supply network. In some embodiments, the system
comprises a cyber-safety and security system. In some embodiments,
the system comprises a real-time communication function.
In some embodiments, the RSU network comprises an RSU and/or an RSU
subsystem. In some embodiments, an RSU comprises one or more of: a
sensing module configured to measure characteristics of the driving
environment; a communication module configured to communicate with
vehicles, TCUs, and the cloud; a data processing module configured
to process, fuse, and compute data from the sensing and/or
communication modules; an interface module configured to
communicate between the data processing module and the
communication module; and an adaptive power supply module
configured to provide power and to adjust power according to the
conditions of the local power grid. In some embodiments, the
adaptive power supply module is configured to provide backup
redundancy. In some embodiments, a communication module
communicates using wired or wireless media. See, e.g., U.S. patent
application Ser. No. 16/135,916, incorporated herein by
reference.
In some embodiments, a sensing module comprises a radar based
sensor. In some embodiments, a sensing module comprises a vision
based sensor. In some embodiments, a sensing module comprises a
radar based sensor and a vision based sensor and wherein said
vision based sensor and said radar based sensor are configured to
sense the driving environment and vehicle attribute data. In some
embodiments, the radar based sensor is a LIDAR, microwave radar,
ultrasonic radar, or millimeter radar. In some embodiments, the
vision based sensor is a camera, infrared camera, or thermal
camera. In some embodiments, the camera is a color camera. See,
e.g., U.S. patent application Ser. No. 16/135,916, incorporated
herein by reference.
In some embodiments, the sensing module comprises a satellite based
navigation system and/or is configured to receive data from a
satellite based navigation system. In some embodiments, the sensing
module comprises an inertial navigation system. In some
embodiments, the sensing module comprises a satellite based
navigation system and an inertial navigation system and wherein
said sensing module comprises a satellite based navigation system
and said inertial navigation system are configured to provide
vehicle location data. In some embodiments, the satellite based
navigation system is a Differential Global Positioning System
(DGPS) or a BeiDou Navigation Satellite System (BDS) System or a
GLONASS Global Navigation Satellite System. In some embodiments,
the inertial navigation system comprises an inertial reference
unit. See, e.g., U.S. patent application Ser. No. 16/135,916,
incorporated herein by reference.
In some embodiments, the sensing module comprises a vehicle
identification device. In some embodiments, the vehicle
identification device is configured to receive vehicle
identification data from an RFID component, Bluetooth component,
Wi-fi (IEEE 802.11) component, or a cellular network radio, e.g., a
4G or 5G cellular network radio. See, e.g., U.S. patent application
Ser. No. 16/135,916, incorporated herein by reference.
In some embodiments, the RSU is deployed at a fixed location near
road infrastructure (e.g., near a critical point; near a
non-critical point). In some embodiments, the RSU is deployed at a
critical point, e.g., at a highway roadside, a highway on ramp, a
highway off ramp, an interchange, a bridge, a tunnel, a toll
station, or on a drone over a critical point. In some embodiments,
the RSU is deployed on a mobile component. In some embodiments, the
RSU is deployed on a vehicle drone or on an unmanned aerial vehicle
(UAV) over a critical location (e.g., a dynamic critical point),
e.g., at a site of traffic congestion, at a site of a traffic
accident, at a site of highway construction, or at a site of
extreme weather. In some embodiments, a RSU is positioned according
to road geometry, heavy vehicle size, heavy vehicle dynamics, heavy
vehicle density, and/or heavy vehicle blind zones. In some
embodiments, the RSU is installed on a gantry (e.g., an overhead
assembly, e.g., on which highway signs or signals are mounted). In
some embodiments, the RSU is installed using a single cantilever or
dual cantilever support.
In some embodiments, the TCC network is configured to provide
traffic operation optimization, data processing, and data
archiving. In some embodiments, the TCC network comprises a human
operations interface. In some embodiments, the TCC network is a
macroscopic TCC, a regional TCC, or a corridor TCC based on the
geographical area covered by the TCC network. See, e.g., U.S.
patent application Ser. No. 15/628,331, filed Jun. 20, 2017, and
U.S. Provisional Patent Application Ser. Nos. 62/626,862, filed
Feb. 6, 2018, 62/627,005, filed Feb. 6, 2018, 62/655,651, filed
Apr. 10, 2018, and 62/669,215, filed May 9, 2018, each of which is
incorporated herein in its entirety for all purposes.
In some embodiments, the TCU network is configured to provide
real-time vehicle control and data processing. In some embodiments,
the real-time vehicle control and data processing are automated
based on preinstalled algorithms.
In some embodiments, the TCU network comprises segment TCU and/or
point TCUs based on the geographical area covered by the TCU
network. See, e.g., U.S. patent application Ser. No. 15/628,331,
filed Jun. 20, 2017 and U.S. Provisional Patent Application Ser.
Nos. 62/626,862, filed Feb. 6, 2018, 62/627,005, filed Feb. 6,
2018, 62/655,651, filed Apr. 10, 2018, and 62/669,215, filed May 9,
2018, each of which is incorporated herein in its entirety for all
purposes. In some embodiments, the system comprises a point TCU
physically combined or integrated with an RSU. In some embodiments,
the system comprises a segment TCU physically combined or
integrated with a RSU.
In some embodiments, the TCC network comprises macroscopic TCCs
configured to process information from regional TCCs and provide
control targets to regional TCCs; regional TCCs configured to
process information from corridor TCCs and provide control targets
to corridor TCCs; and corridor TCCs configured to process
information from macroscopic and segment TCUs and provide control
targets to segment TCUs. See, e.g., U.S. patent application Ser.
No. 15/628,331, filed Jun. 20, 2017 and U.S. Provisional Patent
Application Ser. Nos. 62/626,862, filed Feb. 6, 2018, 62/627,005,
filed Feb. 6, 2018, 62/655,651, filed Apr. 10, 2018, and
62/669,215, filed May 9, 2018, each of which is incorporated herein
in its entirety for all purposes.
In some embodiments, the TCU network comprises: segment TCUs
configured to process information from corridor and/or point TOCs
and provide control targets to point TCUs; and point TCUs
configured to process information from the segment TCU and RSUs and
provide vehicle-based control instructions to an RSU. See, e.g.,
U.S. patent application Ser. No. 15/628,331, filed Jun. 20, 2017
and U.S. Provisional Patent Application Ser. Nos. 62/626,862, filed
Feb. 6, 2018, 62/627,005, filed Feb. 6, 2018, 62/655,651, filed
Apr. 10, 2018, and 62/669,215, filed May 9, 2018, each of which is
incorporated herein in its entirety for all purposes. See, e.g.,
U.S. patent application Ser. No. 16/135,916, incorporated herein by
reference.
In some embodiments, the RSU network, a RSU (e.g., a full function
RSU or a limited function RSU) provides vehicles with customized
traffic information and control instructions and/or receives
information provided by vehicles. In some embodiments, a limited
function RSU communicates information with vehicles but does not
provide control instructions to vehicles. In some embodiments, a
limited function RSU provides control instructions to vehicles but
does not communicate information with vehicles.
In some embodiments, the TCC network comprises one or more TCCs
comprising a connection and data exchange module configured to
provide data connection and exchange between TCCs. In some
embodiments, the connection and data exchange module comprises a
software component providing data rectify, data format convert,
firewall, encryption, and decryption methods. In some embodiments,
the TCC network comprises one or more TCCs comprising a
transmission and network module configured to provide communication
methods for data exchange between TCCs. In some embodiments, the
transmission and network module comprises a software component
providing an access function and data conversion between different
transmission networks within the cloud platform. In some
embodiments, the TCC network comprises one or more TCCs comprising
a service management module configured to provide data storage,
data searching, data analysis, information security, privacy
protection, and network management functions. In some embodiments,
the TCC network comprises one or more TCCs comprising an
application module configured to provide management and control of
the TCC network. In some embodiments, the application module is
configured to manage cooperative control of vehicles and roads,
system monitoring, emergency services, and human and device
interaction.
In some embodiments, the TCU network comprises one or more TCUs
comprising a sensor and control module configured to provide the
sensing and control functions of an RSU. In some embodiments, the
sensor and control module is configured to provide the sensing and
control functions of radar, camera, RFID, and/or V2I
(vehicle-to-infrastructure) equipment. In some embodiments, the
sensor and control module comprises a DSRC, GPS, 4G, 5G, and/or
wifi radio. In some embodiments, the TCU network comprises one or
more TCUs comprising a transmission and network module configured
to provide communication network functions for data exchange
between an automated vehicle and a RSU. In some embodiments, the
TCU network comprises one or more TCUs comprising a service
management module configured to provide data storage, data
searching, data analysis, information security, privacy protection,
and network management. In some embodiments, the TCU network
comprises one or more TCUs comprising an application module
configured to provide management and control methods of an RSU. In
some embodiments, the management and control methods of an RSU
comprise local cooperative control of vehicles and roads, system
monitoring, and emergency service. In some embodiments, the TCC
network comprises one or more TCCs further comprising an
application module and said service management module provides data
analysis for the application module. In some embodiments, the TCU
network comprises one or more TCUs further comprising an
application module and said service management module provides data
analysis for the application module.
In some embodiments, the TOC comprises interactive interfaces. In
some embodiments, the interactive interfaces provide control of
said TCC network and data exchange. In some embodiments, the
interactive interfaces comprise information sharing interfaces and
vehicle control interfaces. In some embodiments, the information
sharing interfaces comprise: an interface that shares and obtains
traffic data; an interface that shares and obtains traffic
incidents; an interface that shares and obtains passenger demand
patterns from shared mobility systems; an interface that
dynamically adjusts prices according to instructions given by said
vehicle operations and control system; an interface that allows a
special agency (e.g., a vehicle administrative office or police) to
delete, change, and share information; and/or an interface that
allows a special agency (e.g., a vehicle administrative office or
police) to identify a critical point at a location on a road. In
some embodiments, the vehicle control interfaces comprise: an
interface that allows said vehicle operations and control system to
assume control of vehicles; an interface that allows vehicles to
form a platoon with other vehicles; and/or an interface that allows
a special agency (e.g., a vehicle administrative office or police)
to assume control of a vehicle. In some embodiments, the traffic
data comprises vehicle density, vehicle velocity, and/or vehicle
trajectory. In some embodiments, the traffic data is provided by
the vehicle operations and control system and/or other share
mobility systems. In some embodiments, traffic incidents comprise
extreme conditions, major accident, and/or a natural disaster. In
some embodiments, a critical point is identified at the location of
a traffic incident. In some embodiments, an interface allows the
vehicle operations and control system to assume control of vehicles
upon occurrence of a traffic event, extreme weather, or pavement
breakdown when alerted by said vehicle operations and control
system and/or other share mobility systems. In some embodiments, an
interface allows vehicles to form a platoon with other vehicles
when they are driving in the same dedicated and/or same
non-dedicated lane.
In some embodiments, the OBU comprises a communication module
configured to communicate with an RSU. In some embodiments, the OBU
comprises a communication module configured to communicate with
another OBU. In some embodiments, the OBU comprises a data
collection module configured to collect data from external vehicle
sensors and internal vehicle sensors; and to monitor vehicle status
and driver status. In some embodiments, the OBU comprises a vehicle
control module configured to execute control instructions for
driving tasks. In some embodiments, the driving tasks comprise car
following and/or lane changing. In some embodiments, the control
instructions are received from an RSU. In some embodiments, the OBU
is configured to control a vehicle using data received from an RSU.
In some embodiments, the data received from said RSU comprises:
vehicle control instructions; travel route and traffic information;
and/or services information. In some embodiments, the vehicle
control instructions comprise a longitudinal acceleration rate, a
lateral acceleration rate, and/or a vehicle orientation. In some
embodiments, the travel route and traffic information comprise
traffic conditions, incident location, intersection location,
entrance location, and/or exit location. In some embodiments, the
services data comprises the location of a fuel station and/or
location of a point of interest. In some embodiments, OBU is
configured to send data to an RSU. In some embodiments, the data
sent to said RSU comprises: driver input data; driver condition
data; vehicle condition data; and/or goods condition data. In some
embodiments, the driver input data comprises origin of the trip,
destination of the trip, expected travel time, service requests,
and/or level of hazardous material. In some embodiments, the driver
condition data comprises driver behaviors, fatigue level, and/or
driver distractions. In some embodiments, the vehicle condition
data comprises vehicle ID, vehicle type, and/or data collected by a
data collection module. In some embodiments, the goods condition
data comprises material type, material weight, material height,
and/or material size.
In some embodiments, the OBU is configured to collecting data
comprising: vehicle engine status; vehicle speed; goods status;
surrounding objects detected by vehicles; and/or driver conditions.
In some embodiments, the OBU is configured to assume control of a
vehicle. In some embodiments, the OBU is configured to assume
control of a vehicle when the automated driving system fails. In
some embodiments, the OBU is configured to assume control of a
vehicle when the vehicle condition and/or traffic condition
prevents the automated driving system from driving said vehicle. In
some embodiments, the vehicle condition and/or traffic condition is
adverse weather conditions, a traffic incident, a system failure,
and/or a communication failure.
The technology provides traffic sensing and control at a variety of
scales, e.g., at a microscopic level (e.g., to provide traffic
sensing and control for individual vehicles with respect to
longitudinal movements (car following, acceleration and
deceleration, stopping and standing) and lateral movements (lane
keeping, lane changing)); at a mesoscopic level (e.g., to provide
traffic sensing and control for road corridors and segments (e.g.,
special event early notification, incident prediction, weaving
section merging and diverging, platoon splitting and integrating,
variable speed limit prediction and reaction, segment travel time
prediction, and/or segment traffic flow prediction); and at a
macroscopic level (e.g., to provide traffic sensing and control for
a road network (e.g., potential congestion prediction, potential
incident prediction, network traffic demand prediction, network
status prediction, and/or network travel time prediction). Critical
points can be identified by components functioning at the
microscopic, mesoscopic, and/or macroscopic levels.
As shown in FIG. 1, in some embodiments, the technology provides a
CAVH system comprising a TCC/TOC 101, TCU 102, and RSU 103 to
provide control for critical points. For each critical point, RSUs
103 collect static and/or dynamic data from the environment and
send data to TCU 102. TCUs 102 aggregate the data and send the data
(and/or fused (e.g., integrated) data) to TCC/TOC 101. Based on the
data collected, TCC/TOC 101 makes decisions at the macroscopic
control level and sends information and/or control instructions to
TCUs 102. After receiving control instructions, TCUs 102 generate
mesoscopic control strategies and send them to RSU 103. According
to the strategies, RSUs 103 control vehicles at different critical
points. For Stop Sign Critical Point 104, RSU 103 computes a gap
between vehicles on the major road through which vehicles on the
minor road may pass. For Traffic Signal Critical Point 105, RSU 103
adjusts vehicle speeds to maintain and/or control the traffic
capacity of the road. For Traffic Oscillation Critical Point 106,
RSU 103 controls the speed of vehicle platoons to reduce traffic
saturation. For Traffic Capacity Critical Point 107, RSU 103
reroutes vehicles from the minor road to maintain the major road at
a high traffic volume.
As shown in FIG. 2, in some embodiments, the technology comprises
components configured to manage information flow for coordinated
control of vehicles. RSU 201 provides location information and
function requirements to control module 204 along with sensed
static object information and sensed dynamic object information
(e.g., data from sensors characterizing and/or identifying moving
objects in the environment (e.g., dynamic objects) and non-moving
objects in the environment (e.g., static objects). TCC/TCU 202
conveys real-time traffic information, accidents and special events
information, instructions and recommendations from decision-makers,
and control levels to control module 204 to facilitate control
process. Control module 204 also receives information from the
cloud and other sources 203 for calculating control strategies
and/or to provide control instructions.
As shown in FIG. 3, in some embodiments, the technology comprises
components configured to identify critical points in a road system.
For example, embodiments provide that the system compares
information and/or sensor data characterizing a location on a road
to determine if the location satisfies the criteria for a static
critical point (e.g., historical crash data, traffic sign, traffic
signal, road configuration, etc.). If the location satisfies the
criteria for a static critical point, the location is identified as
a critical point. If the location does not satisfy the criteria for
a static critical point, the system compares information and/or
sensor data characterizing the location to determine if the
location satisfies the criteria for a dynamic critical point
(traffic oscillations, real-time traffic incident, etc.). If the
location satisfies the criteria for a dynamic critical point, the
location is identified as a critical point. If the location does
not satisfy the criteria for a dynamic critical point, the location
will be identified as a non-critical point.
As shown in FIG. 4, in some embodiments, the technology comprises a
component configured to synchronize sensor data. The
synchronization module 402 receives sensor data from sensors 401
and synchronizes these data in time and/or synchronizes these data
with respect to location (e.g., space synchronization).
Synchronized data are provided to control module 403 for use in
controlling vehicles in the system. In some embodiments, sensor
frequency is used to synchronize sensor data in time.
As shown in FIG. 5, in some embodiments, the technology provides
systems and methods for managing traffic at an intersection
comprising a traffic signal. In some embodiments, systems comprise
a limited function RSU 502 at a signalized intersection with
permitted left-turn phases. During each signal phase, there are
potential conflict points between vehicles moving through the
intersection. For example, vehicles turning left and oncoming
vehicles moving straight through the intersection (FIG. 5, shaded
trajectories) would have a conflict point during this phase. In
some embodiments, the limited function RSU 502 coordinates with the
signal controller 507 to pre-identify conflict points at an
intersection. When a first vehicle 503 and a second vehicle 504
approach the intersection with critical movements, the RSU 502
communicates with those vehicles (e.g., by wireless communication
501) and provides the vehicles with information and control
instructions to guide the vehicles through the intersection safely
and efficiently. For example, in some embodiments, the system sends
a starting time to non-CAVH vehicles approaching the intersection
with critical movements (e.g., vehicle 503) and sends a control
strategy to the CAVH vehicles approaching the intersection with
critical movements (e.g., vehicle 504). Meanwhile, the limited
function RSU would not communication with and/or provide
instructions to vehicles approaching the intersection with
non-critical movements (e.g., vehicles 505 and 506) to preserve
resources for providing instructions to vehicles approaching the
intersection with critical movements.
As shown in FIG. 6, in some embodiments the technology provides
systems and methods for managing traffic at an intersection
comprising a stop sign (e.g., a 4-way stop intersection). In some
embodiments, systems comprise a limited function RSU 602 at a 4 way
stop sign intersection. The vehicle trajectories 603 cause conflict
points in the stop sign intersection. The limited function RSU 602
identifies conflict points in the stop sign intersection. Then the
RSU communicates with the nearby vehicles (e.g., by wireless
communication 601) and provides information and/or control
instructions to the nearby vehicles to guide the vehicles through
the stop sign intersection.
As shown in FIG. 7, in some embodiments, the technology provides
systems and methods for managing traffic at a roundabout. Vehicle
trajectories of vehicles in the roundabout, approaching the
roundabout, and exiting the roundabout (e.g., vehicles 702 and 703)
potentially cause conflict points in the roundabout. One or more
RSUs 704 are positioned near conflict points of a roundabout. The
RSUs 704 identify and sense the areas near the conflict point.
Then, the RSU sends information about the conflicted areas to the
nearby connected vehicles (e.g., by wireless communication 701) and
helps those connected vehicles travel through the roundabout.
The technology provides systems and methods for managing traffic
and controlling vehicles on roadway systems. In particular, the
technology provides systems, components of systems, and methods for
managing traffic and controlling vehicles on a variety of road
types, on roadway systems comprising a variety of different road
types (e.g., for managing traffic and controlling vehicles that
move among various road types). For example, embodiments of the
technology relate to managing traffic and controlling vehicles on
roads having a range of traffic volumes (e.g., high volume, low
volume, moderate volume, varying volume), a range of vehicle and
traffic types (e.g., autonomous, non-autonomous, pedestrian, heavy
vehicle, platoon, bicycle, etc.), different road components (e.g.,
intersections, curves, straight portions, on-ramps, off-ramps,
roundabouts, etc.), different traffic control components (e.g.,
traffic signals, stop signs, special traffic lanes, etc.), and for
roads having critical points and for roads that do not have
critical points. In some embodiments, the technology comprises
providing different types of RSUs (e.g., comprising different
sensors and/or different numbers of sensors) for different types of
roads. For example, in some embodiments, regions of roads
comprising a critical point comprise RSUs with a higher level of
functionality (e.g., RSUs provide both traffic control and
information services, RSUs comprise a larger number of sensors,
etc.) to provide increased monitoring, increased data collection,
increased information provision, and increased control of traffic.
In some embodiments, regions of roads comprising a critical point
comprise an increased number of RSUs to provide more coverage by
the CAVH system of the critical point area. In some embodiments,
regions of roads that do not comprise a critical point comprise
RSUs of lower functionality and/or a decreased number of RSUs,
e.g., to conserve resources and/or to allocate resources to areas
comprising a critical point or requiring more traffic management
and vehicle control.
In some embodiments, the technology provides methods and systems to
manage traffic and control vehicles in particular scenarios. For
example, in some embodiments, the technology provides methods and
systems to manage traffic (e.g., mixed traffic) and control
vehicles at a signalized intersection. In some embodiments, the
technology provides methods comprising collecting information
(e.g., by CAVH sensors (e.g., by RSU sensors and/or by vehicle
sensors)) at a signalized intersection. In some embodiments, the
technology provides systems configured to collect information
(e.g., by CAVH sensors (e.g., by RSU sensors and/or by vehicle
sensors)) at a signalized intersection. In some embodiments,
technology for information collection and sensing at a signalized
intersection comprises an intersection RSU that collects
information and data from communicating with vehicles within range
of the intersection, upper level IRIS servers (e.g., TCU/TCC), and
the regional traffic signal system. Furthermore, the intersection
RSU comprises sensing devices and acquires data through the sensing
devices. In some embodiments, the technology provides methods
comprising predicting and/or managing transportation behavior
(e.g., predicting traffic patterns and vehicle trajectories),
making decisions on traffic management and vehicle control
strategies and instructions, and choosing algorithms and models for
prediction and making decisions at a signalized intersection. In
some embodiments, the technology provides systems configured to
predict and/or manage transportation behavior (e.g., predict
traffic patterns and vehicle trajectories), make decisions on
traffic management and vehicle control strategies and instructions,
and choose algorithms and models for prediction and making
decisions at a signalized intersection. In some embodiments,
technology for prediction and decision making at a signalized
intersection assesses collected (e.g., aggregated and/or
integrated) information (e.g., historical data, real-time data
provided by CAVH system (e.g., data provided by RSUs, data provided
by vehicles, data provided by upper level IRIS servers (e.g.,
TCU/TCC)), chooses an algorithm and/or model, and provides traffic
management and/or vehicle control instructions (e.g., optimized for
the traffic scenario) for the vehicles within range of the
signalized intersection. In some embodiments, methods comprise
controlling and/or distributing information relating to a
signalized intersection. In some embodiments, systems are
configured to control and/or distribute information relating to a
signalized intersection. In some embodiments, technology for
control and/or distribution of information relating to a signalized
intersection comprises sending control messages to vehicles
configured to follow automation orders (e.g., vehicles comprising
an OBU). In some embodiments, other vehicles with V2I capabilities
receive relevant traffic information and/or driving instructions.
In some embodiments, mesoscopic (e.g., platoon control and
organization; coordinating traffic with traffic signals at the
intersection) and microscopic level control for individual vehicle
(e.g., steering, braking, and/or acceleration instructions; and/or
longitude and latitude parameters to follow) are implemented.
As described herein, the CAVH technology provides that critical
points (e.g., road areas where vehicles from different directions
may conflict (e.g., at a signalized intersection)) comprise an
increased deployment of sensing devices (e.g., increased number of
RSUs and/or RSUs comprising an increased number of sensors). The
locations of vehicle conflict at a critical point vary in time
and/or in location. In particular, the locations and times of
vehicle conflict are a function of vehicle movements, the traffic
signal control, and/or the design of the intersection and
signalization of the intersection. Accordingly, these factors are
provided as information to implement the types and number of
sensing devices (e.g., RSUs) at signalized intersections.
Furthermore, in some embodiments, the technology provides methods
and systems to manage traffic (e.g., mixed traffic) and control
vehicles travelling on a freeway. In some embodiments, the
technology provides methods comprising collecting information
(e.g., by CAVH sensors (e.g., by RSU sensors and/or by vehicle
sensors)) on a freeway. In some embodiments, the technology
provides systems configured to collect information (e.g., by CAVH
sensors (e.g., by RSU sensors and/or by vehicle sensors)) on a
freeway. In some embodiments, technology for information collection
and sensing on a freeway comprises a freeway RSU that collects
information and data from communicating with vehicles within range
of the freeway section, upper level IRIS servers (e.g., TCU/TCC),
and the regional traffic signal system. Furthermore, the freeway
RSU comprises sensing devices and acquires data through the sensing
devices. For example, in some embodiments, the RSU senses the road
conditions and/or the composition of the mixed traffic stream on
the freeway (e.g., numbers and types (e.g., distribution) of
vehicles (e.g., autonomous, non-autonomous, heavy, platooned,
etc.)) In some embodiments, the technology provides methods
comprising predicting and/or managing transportation behavior
(e.g., predicting traffic patterns and vehicle trajectories),
making decisions on traffic management and vehicle control
strategies and instructions, and choosing algorithms and models for
prediction and making decisions for vehicles on a freeway. In some
embodiments, the technology provides systems configured to predict
and/or manage transportation behavior (e.g., predict traffic
patterns and vehicle trajectories), make decisions on traffic
management and vehicle control strategies and instructions, and
choose algorithms and models for prediction and making decisions
for vehicles on a freeway. In some embodiments, technology for
prediction and decision making on a freeway assesses collected
(e.g., aggregated and/or integrated) information (e.g., historical
data, real-time data provided by CAVH system (e.g., data provided
by RSUs, data provided by vehicles, data provided by upper level
IRIS servers (e.g., TCU/TCC)), chooses an algorithm and/or model,
and provides traffic management and/or vehicle control instructions
(e.g., optimized for the traffic scenario) for the vehicles within
range of the freeway section. In some embodiments, methods comprise
controlling and/or distributing information relating to a freeway.
In some embodiments, systems are configured to control and/or
distribute information relating to a freeway. In some embodiments,
technology for control and/or distribution of information relating
to a freeway comprises sending control messages (e.g., from a
TCC/TCU) to vehicles configured to follow automation orders (e.g.,
vehicles comprising an OBU). In some embodiments, other vehicles
with V2I capabilities receive relevant traffic information (e.g.,
real-time traffic information) and/or driving instructions for the
freeway section. In some embodiments, mesoscopic (e.g., platoon
control and organization) and microscopic level control for
individual vehicle (e.g., steering, braking, and/or acceleration
instructions; and/or longitude and latitude parameters to follow)
are implemented.
In some embodiments, the technology provides methods and systems to
manage traffic (e.g., mixed traffic) and control vehicles at a stop
sign or yield sign intersection. In some embodiments, the
technology provides methods comprising collecting information
(e.g., by CAVH sensors (e.g., by RSU sensors and/or by vehicle
sensors)) at a stop sign or yield sign intersection (e.g., by RSU
near the stop sign or yield sign). In some embodiments, the
technology provides systems configured to collect information
(e.g., by CAVH sensors (e.g., by RSU sensors and/or by vehicle
sensors)) at a stop sign or yield sign intersection (e.g., by RSU
near the stop sign or yield sign). Furthermore, the intersection
RSU comprises sensing devices and acquires data through the sensing
devices. In some embodiments, technology for information collection
and sensing at a stop sign or yield sign intersection comprises an
intersection RSU that collects information and data from
communicating with vehicles within range of the intersection, upper
level IRIS servers (e.g., TCU/TCC), the regional traffic signal
system, and sensing the intersection area near the stop sign or
yield sign for data and information using RSU sensors and/or
sensors on a vehicle. In some embodiments, the technology provides
methods comprising predicting and/or managing transportation
behavior (e.g., predicting traffic patterns and vehicle
trajectories), making decisions on traffic management and vehicle
control strategies and instructions, and choosing algorithms and
models for prediction and making decisions at a stop sign or yield
sign intersection to manage traffic flow through the stop sign or
yield sign intersection. In some embodiments, the technology
provides systems configured to predict and/or manage transportation
behavior (e.g., predict traffic patterns and vehicle trajectories),
make decisions on traffic management and vehicle control strategies
and instructions, and choose algorithms and models for prediction
and making decisions at a stop sign or yield sign intersection to
manage traffic flow through the stop sign or yield sign
intersection. In some embodiments, technology for prediction and
decision making at a signalized intersection assesses collected
(e.g., aggregated and/or integrated) information (e.g., historical
data, real-time data provided by CAVH system (e.g., data provided
by RSUs, data provided by vehicles, data provided by upper level
IRIS servers (e.g., TCU/TCC)), chooses an algorithm and/or model,
and provides traffic management and/or vehicle control instructions
(e.g., optimized for the traffic scenario) for the vehicles within
range of the stop sign or yield sign intersection. In some
embodiments, methods comprise controlling and/or distributing
information relating to a stop sign or yield sign intersection. In
some embodiments, systems are configured to control and/or
distribute information relating to a stop sign or yield sign
intersection. In some embodiments, technology for control and/or
distribution of information relating to a stop sign or yield sign
intersection comprises sending control messages to vehicles
configured to follow automation orders (e.g., vehicles comprising
an OBU). In some embodiments, other vehicles with V2I capabilities
receive relevant traffic information and/or driving instructions.
In some embodiments, mesoscopic (e.g., vehicle movement and
organization; platoon control; coordinating traffic movement with
movement of pedestrians crossing roads at the stop sign or yield
sign intersection) and microscopic level control for individual
vehicle (e.g., steering, braking, and/or acceleration instructions;
and/or longitude and latitude parameters to follow) are
implemented.
In some embodiments, the technology provides methods and systems to
manage traffic and control vehicles at a roundabout (e.g., entering
into, exiting from, and/or traveling within a roundabout). For
example, in some embodiments, the technology provides methods and
systems to manage traffic (e.g., mixed traffic) and control
vehicles at a roundabout. In some embodiments, the technology
provides methods comprising collecting information (e.g., by CAVH
sensors (e.g., by RSU sensors and/or by vehicle sensors)) at a
roundabout. In some embodiments, the technology provides systems
configured to collect information (e.g., by CAVH sensors (e.g., by
RSU sensors and/or by vehicle sensors)) at a roundabout. In some
embodiments, technology for information collection and sensing at a
signalized intersection comprises a roundabout RSU (e.g., a
plurality of roundabout RSUs) that collects information and data
from communicating with vehicles at the roundabout, upper level
IRIS servers (e.g., TCU/TCC), and sensing the areas near the
roundabout (e.g., by RSU sensors or vehicle onboard sensors).
Accordingly, in some embodiments, a roundabout RSU comprises
sensing devices and acquires data through the sensing devices. In
some embodiments, the technology provides methods comprising
predicting and/or managing transportation behavior (e.g.,
predicting traffic patterns and vehicle trajectories), making
decisions on traffic management and vehicle control strategies and
instructions, and choosing algorithms and models for prediction and
making decisions at a roundabout. In some embodiments, the
technology provides systems configured to predict and/or manage
transportation behavior (e.g., predict traffic patterns and vehicle
trajectories), make decisions on traffic management and vehicle
control strategies and instructions, and choose algorithms and
models for prediction and making decisions at a roundabout. In some
embodiments, technology for prediction and decision making at a
roundabout assesses collected (e.g., aggregated and/or integrated)
information (e.g., historical data, real-time data provided by CAVH
system (e.g., data provided by RSUs, data provided by vehicles,
data provided by upper level IRIS servers (e.g., TCU/TCC)), chooses
an algorithm and/or model, and provides traffic management and/or
vehicle control instructions (e.g., optimized for the traffic
scenario) for the vehicles at the roundabout. In some embodiments,
methods comprise controlling and/or distributing information
relating to a signalized intersection. In some embodiments, systems
are configured to control and/or distribute information relating to
a roundabout. In some embodiments, technology for control and/or
distribution of information relating to a roundabout comprises
sending control messages to vehicles configured to follow
automation orders (e.g., vehicles comprising an OBU). In some
embodiments, other vehicles with V2I capabilities receive relevant
traffic information and/or driving instructions. In some
embodiments, mesoscopic (e.g., platoon control and organization;
coordination of roundabout traffic with traffic signals) and
microscopic level control for individual vehicle (e.g., steering,
braking, and/or acceleration instructions; and/or longitude and
latitude parameters to follow) are implemented.
As described herein, the CAVH technology provides that critical
points (e.g., road areas where vehicles from different directions
may conflict (e.g., at a roundabout)) comprise an increased
deployment of sensing devices (e.g., increased number of RSUs
and/or RSUs comprising an increased number of sensors). The
locations of vehicle conflict at a critical point vary in time
and/or in location. In particular, the locations and times of
vehicle conflict are a function of vehicle movements, the traffic
signal control, and/or the design of the roundabout and
signalization of the roundabout. Accordingly, these factors are
provided as information to implement the types and number of
sensing devices (e.g., RSUs) at a roundabout. As a particular
example, there are 8 total conflict points at a typical 4-leg
roundabout--4 merging and 4 diverging.
* * * * *